DATA ANALYSIS

Data Analysis

Learn how data analysis and the insights extracted from big data are helping companies and municipalities lead with deeper intelligence.

What is Data Analysis?

There's a data revolution taking place across the globe in industries as diverse as fashion, automotive, retail, and insurance. Entire industries are changing through digital innovation, including:

Enhanced service and customer interaction models

New manufacturing and operations systems

Innovative products and applications

Business-critical finance and investment decision-making

The new business imperative to execute real-time data analysis of massive amounts of information is leaving some companies and organization struggling to keep up.

In retail, for example, companies are processing data on global sales transactions and product performance; financial institutions and insurance companies are using real-time data analysis to enhance security and curb fraud; automotive manufacturers are analyzing vehicle performance and enhancing safety through advanced analytics.
As data collection platforms have evolved, internet- and network- related data is being generated at faster rates than ever, a trend that shows no signs of slowing. And as organizations generate more and more data in abundance, the burden shifts to sophisticated and smart data analysis platforms - companies can be rich in data and but poor in intelligence. It’s the incisive analysis of that "big data" that will lead to smarter decisions and clearer results.

Thinking about data as anasset often requires a real mindset shift for most companies and organizations. For an enterprise to move from passive collector to active analyzer of data—and be truly data-driven—it must assemble the data analysis tools and talent to manage the data at speed and at scale. The following content will examine how the proper analysis of big data flows can generate true insights for organizations, both in the public and private sectors.

DATA ANALYSIS PLATFORM

How can your enterprise harness business-critical information to make smart, strategic decisions? How can you tap into a wealth of knowledge, without a huge investment of time and money?

At Accenture Applied Intelligence, we work at the intersection of technology and business-helping our clients become insights-driven enterprises. The Accenture Insights Platform is fast, flexible and scalable-ready to transform performance in weeks, not years.

By drawing on pre-configured technologies and in-depth experience, the Accenture Insights Platform is designed for rapid mobilization. It gives you a complete turnkey solution, quickly and efficiently. Your organization becomes on its way to enlightening and empowering your people with always-on data.

Accenture Insights Platform hosts an advanced analytics applications portfolio, an integrated design, build, run environment enabling the agile development of industry and function-specific analytics solutions. The applications are flexible, easily tailored and agile, providing organizations with immediate access to the tools needed to make data-driven decisions and solve complex business issues.

The Accenture Connected Analytics Experience is an immersive and collaborative analytics capability that makes data more accessible and engaging, helping insight-driven businesses make faster, more informed decisions.

With a more immersive, innovative approach to data, we bring a new energy to analytics discussions. The result? More collaboration. More engagement. More knowledge.

Big Data

Organizations that start and complete big data projects see practical results and significant value, according to a recent study by Accenture Applied Intelligence. Those standing on the sidelines may be left behind.

Executives report big data delivering business outcomes for a wide spectrum of strategic corporate goals—from new revenue generation and new market development to enhancing the customer experience and improving enterprise-wide performance. Organizations regard big data as extremely important and central to their digital strategy.

To learn more about how organizations are using big data to transform their business today,

"The big in ‘big data’ means different things to different companies. It is far more important to focus on the data that your organization can or should be collecting and work out how best to exploit them.”

Public Sector Case Study

Thames Water is responsible for supplying public water and wastewater management for much of Greater London and the Thames Valley. By tapping the power of their data through Smart Grid analysis, the company was finally able to see all their operations in real-time and ultimately improve their overall performance.

Utilities like Thames Water face increasing pressure to improve customer service, strengthen resilience and deliver security of supply. Despite significant investments in data systems to support responsiveness, the utility couldn’t get out ahead of its information to make better, more informed decisions using advanced data analysis. The challenges of this intelligence lag were clear:

High operational costs to repair failures

High capital costs to build extra capacity

Increased risk of non-compliance and customer complaints

Having already made commitments to implement price reductions, how could Thames Water address these challenges and deliver the investments needed to improve today’s service and tomorrow’s resilience?

"The convergence of a wide range of digital technologies used to manage its infrastructure, will give Thames Water greater flexibility to respond to varying operating conditions, such as fluctuations in demand and changing weather patterns.”

SULEMAN ALLI

​Managing Director
Accenture Water Utilities Industry Group

A Smarter Grid for Greater London

The Smart Grid project’s mission was the help Thames Water use data to provide efficient, high-quality customer service. Smart Grid helped create a single view of the company’s operating systems and assets, such as pipe and treatment facilities.

Analysis of the company’s big data enables more efficient water sourcing and remote asset monitoring. This intelligence helps the utility giant anticipate equipment failures and respond in near real-time to critical situations, such as leaks or adverse weather events.

Private Sector Case Studies

"Customer insights and targeting are currently the highest priority for the application of big data—cited by 42 percent of C-level executives, followed by financial planning with 32 percent and sales with 29 percent.”

A vision for the communications industry

Finance and Risk Analytics

Fighting Crime with Analytics

Data At Work—In London’s Metropolitan Police

The concept of intelligence-led policing is not new and many forces already make the most of proven techniques, such as hotspot and time series analysis. However, with the full integration of data analysis into police operations, important insights can be generated for the first time without the need for large teams of intelligence analysts.

Employing around 31,000 officers alongside 13,000 police staff and 2,600 Police Community Support Officers (PCSOs), the Metropolitan Police Service has a vision: To make London the safest major city in the world. In 2013, the Metropolitan Police Service engaged a pilot program to develop police solutions that involved analytics to fight gang crime in London.

Precisely targeted crime fighting

According to Metropolitan Police Service figures, gangs were responsible for approximately 22 percent of serious violence, 17 percent of robberies, 50 percent of shooting incidents and 14 percent of rape in London in 2012.

By deploying predictive techniques to analyze the data they hold, the London Police could:

Guard against the escalation of particular events by predicting which events are most likely to escalate

Deploy personnel to where they are needed most, improving prevention capability and controlling costs

Conduct and focus new investigations more efficiently

Discover patterns in data that suggest areas for further investigation

Delivering information to the field where and when it's needed

Conducted over a twenty-week period, the pilot program merged and assessed data from various crime reporting and criminal intelligence systems used by the Metropolitan Police Service from the period 2009 to 2012. The program further aimed to prove to the Metropolitan Police Service that predictive analytics could bring an unprecedented level of insight and intelligence that, once deployed, could help reduce gang-related crimes in the city.

"The study used data gathered about known gang members across London’s 32 boroughs across a four year period to forecast their likelihood of committing further violent acts.”

Data Analysis Summary

Re-centering your organization

The data and analytics journey is a cultural journey for your organization. For companies that decide to take that journey, the results can be compelling. From shrinking market share to expanding market share, from pricing pressures to enhanced cost and cash advantage, from customer defection to customer loyalty, from fraud and non-compliance to reduction of fraud and risk, and from fragmentation and complexity to speed-to-insights.

Data is the business of every single person in your company. Organizations that have embraced this change at every level report being very satisfied with the business outcomes of their journey.

"A data-driven culture can’t be built on a few experts. It requires buy-in across an organization, which in turn requires educating employees about the power of data, and empowering them through training.”

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